Change Github link to specific folder, change task category to `image-text-to-text`
#2
by
nielsr
HF Staff
- opened
README.md
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license: apache-2.0
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task_categories:
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- image-to-text
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language:
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- en
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size_categories:
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- 1K<n<10K
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# DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs for Knowledge-Intensive Visual Grounding
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@@ -14,11 +14,8 @@ Xinyu Ma, Ziyang Ding, Zhicong Luo, Chi Chen, Zonghao Guo, Derek F. Wong, Xiaoyi
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<a href='https://deepperception-kvg.github.io/'><img src='https://img.shields.io/badge/Project-Page-blue'></a>
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<a href='https://arxiv.org/abs/2503.12797'><img src='https://img.shields.io/badge/Paper-PDF-Green'></a>
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<a href='https://github.com/
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<a href='https://huggingface.co/MaxyLee/DeepPerception'><img src='https://img.shields.io/badge/Model-Huggingface-yellow'></a>
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<a href='https://huggingface.co/datasets/MaxyLee/KVG'><img src='https://img.shields.io/badge/Dataset-Huggingface-purple'></a>
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This is the official repository of **KVG-Bench**, a comprehensive benchmark of Knowledge-intensive Visual Grounding (KVG) spanning 10 categories with 1.3K manually curated test cases.
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---
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language:
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- en
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license: apache-2.0
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size_categories:
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- 1K<n<10K
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task_categories:
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- image-text-to-text
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pretty_name: KVG-Bench
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---
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# DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs for Knowledge-Intensive Visual Grounding
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<a href='https://deepperception-kvg.github.io/'><img src='https://img.shields.io/badge/Project-Page-blue'></a>
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<a href='https://arxiv.org/abs/2503.12797'><img src='https://img.shields.io/badge/Paper-PDF-Green'></a>
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<a href='https://github.com/thunlp/DeepPerception/tree/main/DeepPerception/KVG_Bench'><img src='https://img.shields.io/badge/Github-Page-green'></a>
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<a href='https://huggingface.co/MaxyLee/DeepPerception'><img src='https://img.shields.io/badge/Model-Huggingface-yellow'></a>
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<a href='https://huggingface.co/datasets/MaxyLee/KVG'><img src='https://img.shields.io/badge/Dataset-Huggingface-purple'></a>
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This is the official repository of **KVG-Bench**, a comprehensive benchmark of Knowledge-intensive Visual Grounding (KVG) spanning 10 categories with 1.3K manually curated test cases.
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